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Software Consulting & Implementation?
You'll be able to speak directly with the CTO/Founder about your project and find out what opportunities & options you have.
About Aviron
We are a team of problem-solvers and communicators. What does this mean for our clients? Not only are we going to accomplish your project, but you’re going to be informed and confident every step of the way. Our team of experts is passionate about fully understanding your problem, finding solutions, and getting it done. The right way.
If the top of your to-do list screams “hire software engineer!, ” we’d love the opportunity to talk about your goals and problem points.
Proven Software Consulting Services.
Increase in overall revenue after working with Aviron Software
Increase in Google Search Traffic after working with Aviron Software
Insights
How Two Words Broke My LLM-Powered Chat Agent
This blog by Spencer Schneidenbach unpacks how a small but critical wording issue in a parameter description led to unexpected failures when migrating a chat agent from GPT-4o to GPT-4.1. Spencer details the debugging journey through Semantic Kernel, revealing how an LLM took a description literally, resulting in malformed date strings and deserialization errors. The post underscores key lessons about LLM behavior, the importance of strong evaluation practices, and why even description attributes must be treated as carefully crafted prompts.
You Don’t Need a Dev Team to Start. But You’ll Want One to Scale.
In this blog, we explore why AI-powered “vibe coding” is perfect for building fast, but not built to last. If you're an early-stage founder spinning up MVPs with lightning speed, that's a win. However, as soon as real users, security, and scale come into play, things become complicated. This blog explores the limitations of DIY development, the challenges that emerge, and how Aviron helps teams transition from prototypes to production-ready platforms.
When AI Learns to Pause
What if great AI wasn’t just about having the right answer, but knowing when not to answer at all? In this blog, Shiloh unpacks the nuance of designing AI systems that pause with purpose. From handling ambiguity to building trust through interaction, he shares how smart assistants can be more helpful, not by guessing, but by asking. This is where technical design meets human intuition, and where AI becomes truly collaborative.
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